Artificial Intelligence in Project Management by Dr. Khaled A. Hamdy

Artificial Intelligence in Project ManagementKHALED HAMDY, PH.D., PMP

Introduction of Khaled Hamdy

• Civil Engineer• Ph.D. in Engineering• Professional Project Manager, PMP©

• Projects Advisor in RTA

Why am I here talking about

Artificial Intelligence?

Contents

• What is Artificial Intelligence?• Artificial Intelligence in Project Management• Data Mining and Knowledge Engineering

What is AI?

Is it Science?Is it Technology?

Is it Magic?

IS AI MAGIC?

Artificial Intelligence is a Science that uses

Technology to Create Magic

Contents

• What is Artificial Intelligence?• Definition• Different Types of Artificial Intelligence• History of Artificial Intelligence• Theories behind Artificial Intelligence

• Artificial Intelligence in Project Management• Engineering Design • Cost Estimation and Bidding• Planning and Scheduling• Risk Management• Prediction of Project Performance

• Data Mining and Knowledge Engineering

Definition of AI

• AI is a machine’s ability to:

• Perceive

• Reason

• Learn

• Act

Sensors (Perceive)

Environment

Perceptions

Actions

Effectors (Act)

Reason & Learn

Another Definition of AI

• AI is the ability of a computer (or a machine) to perform certain tasks thought to require intelligence including:• Logical deduction and inference

• Learning and adaptation

• Ability to make decisions based on:• Past Experience

• Insufficient Information

• Conflicting Information

• Ability to understand spoken/natural language

Different Types of AI

AI

Cognitive Science

RoboticsNatural

Interface

• Expert Systems• Learning Systems• Fuzzy Logic• Genetic Algorithms• Neural Networks• Intelligent Agents

• Visual Perception• Tactility• Dexterity• Locomotion• Navigation

• Natural Languages• Speech Recognition• Virtual Reality• Multisensory Interfaces

History of AI

• A branch of Computer Science

• Around for Decades

• Term first created in 1956

• One of the definitive references on AI (still used today) was LASTpublished in 1992

• Still used as a text book at MIT

ALVINN learns to Drive in 1989

Computer100 Million FLOPS (Floating-Point Operations per second)1/10 Computing Power of the Apple Watch

20161989

Reasons for AI Prominence

1. Huge Advancements in Technology

Reasons for AI Prominence2. Exceptional (Exponential) Growth in

Computing Power 1980’s – 3 CRAY Supercomputers

2017 – iPhone 7More Powerful than

80’s CRAYS

Advances in Computing• Deep Blue defeated Garry Kasparov –

World Chess Champion in 1997

Advances in Technology & Computing

AI is already Changing our Lives

Artificial Intelligence -The Science behind the Magic

• Algorithms that tell computers and other machines how to think and act intelligently

• Many tools and techniques including:• Knowledge Based Expert System

• Artificial Neural Network

• Genetic Algorithm

• Fuzzy Logic

Knowledge Based Expert System (KBES)• Consist of a Knowledge Base and Inference Engine

• The knowledge base is created by collecting the facts and opinions from Subject Matter Experts

• The Inference Engine utilizes IF-THEN statements to provide expertise

Artificial Neural Network (ANN)

• A machine learning approach that models the human brain and consists of a number of artificial neuronslinked by weighted connections

• ANNs demonstrate the ability to learn, recall, and generalize from training patterns or data (numeric, non-numeric or both).


InputLayer

HiddenLayer (s)

OutputLayer

InputsNumeric or

Non-Numeric

OutputsNumeric or

Non-Numeric

Neuron

Neuron

Connections

Connections


Neuron

Genetic Algorithms (GA)

• Iterative search methods that mimic the natural biological evolution process and/or the social behavior of species.

• GAs utilize the natural evolution processes of selection, mutation and cross-over to arrive at near-optimum solutions to large-scale optimization problems, for which traditional mathematical search techniques may fail.

Genetic Algorithms (GA)

Fuzzy Logic

• Fuzzy logic is an approach to computing based on "degrees of truth" rather than the usual "true or false" (1 or 0) Boolean logic on which the modern computer is based

• A form of many-valued logic in which the truth values of variables may be any real number between 0 and 1

Fuzzy vs Boolean Logic

Boolean Logic

Not Tall (0)

150 cm

Tall (1)

180 cm

Fuzzy Logic

Not veryTall (0.2)

150 cm

Definitely Tall (0.9)

180 cm

Contents


AI in Engineering Design

• ANN to select the most suitable structural system for High Rise Buildings subjected to wind and seismic loads

• GA to optimize the LCC of Buildings in hot climates using different combinations of location, orientation and construction materials

AI in Project Planning• KBES to provide estimates of the duration and

resource requirements for project activities based on expert knowledge

• ANN to automate the sequencing of project activities based on functional requirements.

• GA to optimize the schedule of construction project activities in order to minimize the total cost with resource constraints

• Fuzzy Logic to determine project priorities in the Portfolio Management Process

AI in Cost Estimation

• ANN to estimate the suitable mark-up to increase the possibility of winning tenders

• ANN to predict the possible cost over-runs based on the selected contractor, the competence of the project manager, the project size and the type of contract used

• Fuzzy Logic to optimize the cost-time trade-offs in construction projects

AI in Risk Management

• ANN to estimate the probability of occurrence for project risks allowing a more accurate quantitative approach to risk analysis.

• ANN combined with Monte Carlo Simulation to mimic the human procedure of risk evaluation and adaptation

• Fuzzy Logic to assess risks in Construction projects to model probability distributions

AI in Performance Management

• ANN to predict the performance of future projects based on the project parameters such as the Project Manager’s Competence, the Contractor’s ability and the contracting method used.

• KBES to assess claims and provide expert decisions based on the claim conditions

• Fuzzy Logic to improve Project Management Efficiency in Construction Projects

AI in PMAI Tools Design Planning

CostEstimation

RiskManagement

PerformanceManagement

KBES

ANN

GA

FuzzyLogic

AI in PM

• AI can be and has been used in several applications in Project Management enabling better project performance

• AI can make the life of project managers less (or maybe more) miserable

Contents


Data Mining &Knowledge Engineering

• Sources of Data:• Machine Data• Organizations Data• People Data

• Data-Information-Knowledge-Wisdom

Sources of Data

• Machines

• Organizations

• People

Machine Data• Sources:• Medical Equipment

• Smart Devices

• Sensors

Machine Data• Characteristics:• Extensive

• Tabular

• Detailed

• Can be connected

Organizations Data

• Sources:• Banks & Financial Institutions

• Hospitals

• HR Departments

• Retails Stores

Organizations Data

• Characteristics:• Structured

• In Silos

• Variability

People Data

• Sources:• Facebook

• Twitter

• Instagram

• YouTube

20,000 Years

The time peoplespend on Facebookeveryday

342,239 Years Of Video iswatched everymonth on YouTube

People Data• Characteristics:• Un-Structured (80% of World Data)• Fragmented• Variability• HUGE

How Huge is HUGE?

30+ PB vs 2 PB

Data, Information,Knowledge and Wisdom

Data Mining in Project Management

• Knowledge Discovery in Data (KDD) used to extract useful knowledge from large sets of resources data to improve resource management practices

• Data Mining used to improve Project Cost Estimation and Scheduling for Software Projects

Remember

Artificial Intelligence is aScience that uses Technology to create Magic

Also Remember

DATA is theCurrency of the Future

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Questions

Ask the ComputerIt is Intelligent

What should a Self-Driving Car Do?

Myths about AI

Max Tegmark, President of the Future of Life Institute

Artificial Intelligence in Project Management by Dr. Khaled A. Hamdy

Technology

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